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Generative AI Engineer with less than a year in LLMs & Data Science
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AI Engineer and Artificial Intelligence graduate with experience in machine learning, deep learning, generative AI, and large language models (LLMs). Skilled in developing end-to-end AI solutions, including RAG systems, LLM fine-tuning, intelligent automation, and AI-powered applications. Experienced in model development, evaluation, optimization, and deployment, with a passion for building scalable and impactful AI systems that solve real-world challenges.
Helwan University
Bachelor's Degree · Artificial Intelligence
August 1, 2022 – June 30, 2026
Fixed Solutions, Egypt
Data Science Intern
July 1, 2025 – October 1, 2025
India
Homains, Egypt
Machine Learning Intern
October 1, 2024 – December 1, 2024
India
AI Tutor (GenT)
June 24, 2026 – Present
Designed and implemented a Hybrid RAG system for educational question answering, combining semantic chunking, dense retrieval, BM25 retrieval, Reciprocal Rank Fusion (RRF), metadata-aware retrieval, and cross-encoder reranking to improve retrieval precision and answer grounding. Enhanced knowledge retrieval through automated knowledge graph construction in Neo4j using LLM-based entity and relationship extraction, enabling graph-augmented retrieval and contextual reasoning over educational content. Developed an educational assessment pipeline using teacher-student Knowledge Distillation and LoRA fine-tuning of Qwen2.5-1.5B-Instruct for MCQ generation, incorporating Bloom's Taxonomy-aware content classification and multi-dimensional LLM-as-Judge evaluation (CMQS/QPS).
View ProjectMulti-Org RAG Chatbot
June 24, 2026 – Present
Built a secure multi-organization RAG chatbot with isolated knowledge bases, role-based access control, and support for PDF, DOCX, TXT, and CSV documents. Implemented smart retrieval and generation, with persistent chat history, a user feedback system, and multilingual speech-to-text input.
View ProjectAspect-Based Sentiment Analysis
June 24, 2026 – Present
Fine-tuned Qwen2.5-1.5B-Instruct with LoRA for ABSA on laptop reviews, targeting structured JSON generation of aspect-sentiment pairs. Built a complete pipeline including prompt engineering, token-level label masking, custom data collator, Pydantic schema validation, and detailed evaluation with error analysis.
View ProjectBrain Tumor Segmentation (NeuroVision)
June 24, 2026 – Present
Designed an end-to-end deep learning pipeline for MRI brain tumor detection and segmentation using ResNet50 (classification) and U-Net / ResUNet / VGG16-UNet (segmentation). Deployed as a clinical web platform (NeuroVision) where doctors upload scans and review AI results, and patients access scan history and an AI chatbot.
View ProjectArabic Auto-Correction System
June 24, 2026 – Present
Developed a deep learning system for Arabic spelling and typing error correction using LSTM and transformer-based models. Integrated AraBERT (twhin-BERT-Large) to improve contextual understanding for both Modern Standard Arabic and informal dialects.
View ProjectEEG-Based BCI System
June 24, 2026 – Present
Designed and implemented a Brain-Computer Interface (BCI) system for real-time control using raw EEG signals (Motor Imagery & SSVEP); ranked 7th out of 215 teams nationally.
View ProjectBird Audio Classification
June 24, 2026 – Present
Classified bird species from audio recordings using Log-Mel spectrograms with VGG19, ResNet50, Inception-V1, and ViT models.
View ProjectFacial Emotion Detection
June 24, 2026 – Present
Compared CNN and SVM classifiers for facial emotion recognition on the FER2013 dataset.
View ProjectGenerative AI Professional Program
Digital Egypt Pioneers Initiative (DEPI)
June 1, 2025 – Present
MTC-AIC-3 BCI Competition
Military Technical College
June 1, 2025 – Present
DEPI Program - Top 40 Student & Top 5 Project
Digital Egypt Pioneers Initiative (DEPI)
October 1, 2024 – Present
Microsoft ML Engineer Program
Digital Egypt Pioneers Initiative (DEPI)
April 1, 2024 – Present
NASA Space Apps Cairo
NASA International Space Apps Challenge
October 1, 2023 – Present
Cultural Fit Analysis
The candidate exhibits a strong passion for AI and continuous learning, evidenced by their academic pursuits, multiple certifications (including Generative AI Professional Program), and diverse personal projects. Their involvement in student activities as an instructor and organizer suggests a collaborative spirit and a willingness to share knowledge. The breadth of projects, from educational tools to medical imaging and BCI, indicates adaptability and a wide range of interests within AI, which can contribute positively to a dynamic team environment. The academic nature of most projects and limited professional experience (internships) means cultural fit in a fast-paced industry setting needs further validation.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and a proactive learning approach through numerous personal projects, certifications, and extracurricular activities. Their involvement in student activities as an instructor suggests good communication and leadership potential. The project descriptions indicate an ability to work on complex, multi-faceted problems, which is crucial for operational fit in advanced AI roles. However, the resume does not provide direct evidence of stress handling or team collaboration in a professional setting beyond project descriptions.